Lists available operations with their input and output kinds and optional category filtering, so users can identify compatible analysis steps for a workflow.
List available operations with their input kinds and output kind. Optionally filter by category (intervals, series, filtering, peri-event, correlation, alignment).
| Name | Required | Description | Default |
|---|---|---|---|
| category | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden, and it does disclose the shape of what comes back (operations plus their input/output kinds). However, it never states that this is a read-only query with no side effects, nor anything about permissions or cost — for a list tool the risk is low, but the disclosure is thin.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, zero waste, with the core behavior front-loaded and the optional filter clearly marked as optional. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so the description need not explain return values, and the one parameter's valid values are fully enumerated. The only real gap is the missing handoff to describe_operation, but the tool is callable correctly as written.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the single parameter has no description or enum, so the description is the only source of meaning — and it delivers by enumerating the valid categories (intervals, series, filtering, peri-event, correlation, alignment). It does not say whether matching is exact or case-sensitive, which keeps this short of a 5.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('List available operations') and even specifies what each entry contains ('input kinds and output kind'), which is more than the name conveys. It doesn't explicitly distinguish itself from the sibling describe_operation, so the boundary between listing and describing is left for the agent to infer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
'Optionally filter by category' tells the agent filtering is available but not when filtering is warranted versus listing everything. No mention of the natural follow-up (describe_operation) or of any when-not condition, so usage is implied rather than guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.